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Robust Pareto active suspension design for vehicle vibration model with probabilistic uncertain parameters

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Abstract

Using the robust design of a vehicle vibration model considering uncertainties can elaborately show the effects of those unsure values on the performance of such a model.

In this paper, probabilistic metrics, instead of deterministic metrics, are used for a robust Pareto multi-objective optimum design of five-degree of freedom vehicle vibration model having parameters with probabilistic uncertainties. In order to achieve an optimum robust design against probabilistic uncertainties existing in reality, a multi-objective uniform-diversity genetic algorithm (MUGA) in conjunction with Monte Carlo simulation is used for Pareto optimum robust design of a vehicle vibration model with ten conflicting objective functions. The robustness of the design obtained using such a probabilistic approach is shown and compared with that of the design obtained using deterministic approach.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Faculty of Engineering, The University of Guilan, P.O. Box 3756, Rasht, Iran

    A. Jamali, M. Salehpour & N. Nariman-zadeh

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  1. A. Jamali
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  2. M. Salehpour
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  3. N. Nariman-zadeh
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Correspondence to A. Jamali.

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Jamali, A., Salehpour, M. & Nariman-zadeh, N. Robust Pareto active suspension design for vehicle vibration model with probabilistic uncertain parameters. Multibody Syst Dyn 30, 265–285 (2013). https://doi.org/10.1007/s11044-012-9337-4

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  • DOI: https://doi.org/10.1007/s11044-012-9337-4

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